This disclosure relates to an environmental sensing system relating to reliably identifying vehicle lane position for lane keeping in a fully autonomous vehicle, for example, or a vehicle that is driver-assisted.
Vehicle lane position is increasingly used in modern vehicles for such features as Lane Keep Assist (LKA), Lane Centering (LC) and Traffic Jam Assist (TJA), which incorporates aspects of LKA and LC. During operation, the vehicle's lane position is detected, and the vehicle is maintained within the lane using little or no steering input from the driver. Such features are also needed for autonomously driving vehicles.
In one typical approach, the vehicle's lane position is adjusted by using an environmental sensing system that has one or more cameras and a distance ranging sensor (e.g., LIDAR or radar). Lane marker edges are detected by the sensors, but some sort of vision-based sensor is used as the primary sensor for vehicle control, typically in the form of a front mounted camera which detects the lines and lanes.
Data from the sensors must be reliable in order to maintain control of the vehicle without driver input, or full control of the vehicle must be returned to the driver. Repeated interruptions to autonomous control are undesirable, but must be balanced with the need for highly reliable vehicle control.
One reason for which the current systems “turn off” or hand control back to the driver are that the lane markers are poorly marked with fading paint that cannot be distinguished from the road. Another reason is that sun glare on the front facing sensors can be sufficient to cause sensor “drop-out” in which the sensor can no longer provide reliable data for vehicle control. One approach to address sun glare is to combine overlapping or non-overlapping images from multiple cameras to provide the best available lane marker recognition. The problem with this approach is that the primary sensor may no longer be relied upon for indefinite durations, which is not the best practice and not very reliable.